scholarly journals Agreement of Sedentary Behavior Metrics Derived From Hip- and Thigh-Worn Accelerometers Among Older Adults: With Implications for Studying Physical and Cognitive Health

2021 ◽  
Vol 4 (1) ◽  
pp. 79-88
Author(s):  
John Bellettiere ◽  
Fatima Tuz-Zahra ◽  
Jordan A. Carlson ◽  
Nicola D. Ridgers ◽  
Sandy Liles ◽  
...  
Keyword(s):  
Older Adults ◽  
Health Outcomes ◽  
Sedentary Behavior ◽  
Sedentary Time ◽  
Statistical Significance ◽  
Limits Of Agreement ◽  
Cognitive Health ◽  
Bout Duration ◽  
Breaks In Sedentary Time ◽  
Pearson Correlations

Little is known about how sedentary behavior (SB) metrics derived from hip- and thigh-worn accelerometers agree for older adults. Thigh-worn activPAL (AP) micro monitors were concurrently worn with hip-worn ActiGraph (AG) GT3X+ accelerometers (with SB measured using the 100 counts per minute [cpm] cut point; AG100cpm) by 953 older adults (age 77 ± 6.6, 54% women) for 4–7 days. Device agreement for sedentary time and five SB pattern metrics was assessed using mean error and correlations. Logistic regression tested associations with four health outcomes using standardized (i.e., z scores) and unstandardized SB metrics. Mean errors (AP − AG100cpm) and 95% limits of agreement were: sedentary time −54.7 [−223.4, 113.9] min/day; time in 30+ min bouts 77.6 [−74.8, 230.1] min/day; mean bout duration 5.9 [0.5, 11.4] min; usual bout duration 15.2 [0.4, 30] min; breaks in sedentary time −35.4 [−63.1, −7.6] breaks/day; and alpha −.5 [−.6, −.4]. Respective Pearson correlations were: .66, .78, .73, .79, .51, and .40. Concordance correlations were: .57, .67, .40, .50, .14, and .02. The statistical significance and direction of associations were identical for AG100cpm and AP metrics in 46 of 48 tests, though significant differences in the magnitude of odds ratios were observed among 13 of 24 tests for unstandardized and five of 24 for standardized SB metrics. Caution is needed when interpreting SB metrics and associations with health from AG100cpm due to the tendency for it to overestimate breaks in sedentary time relative to AP. However, high correlations between AP and AG100cpm measures and similar standardized associations with health outcomes suggest that studies using AG100cpm are useful, though not ideal, for studying SB in older adults.

scholarly journals TIME SPENT IN SEDENTARY BEHAVIOR DOMAINS AND PHYSICAL FUNCTION IN U.S. OLDER ADULTS

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S169-S169
Author(s):  
Nancy M Gell ◽  
Erin D Bouldin ◽  
Dori Rosenberg
Keyword(s):  
Older Adults ◽  
Health Outcomes ◽  
Sedentary Behavior ◽  
Physical Function ◽  
Computer Use ◽  
Sedentary Time ◽  
Community Dwelling ◽  
Sample Population ◽  
Linear Regression Models ◽  
Tv Watching

Abstract Previous studies have reported associations of sedentary time with worse health outcomes in older adults. Yet, little is known about the relationships between the contexts of sedentary time and health outcomes. The purpose of this study was to examine associations of physical function with time spent in a variety of sedentary behavior domains. We analyzed data from the 2016 National Health and Aging Trends Study, a nationally representative sample of community-dwelling Medicare beneficiaries. Estimated time being sedentary by domains (e.g., TV watching, computer use, resting/napping, eating, transportation, socializing, sitting and doing hobbies) were collected from a subset of the sample population (N=2157). The Short Physical Performance Battery (SPPB) measured physical function. Linear regression models were conducted adjusting for sociodemographics, health conditions, pain, and dementia. More time watching TV and resting/napping was significantly associated total SPPB scores (p < 0.01). In adjusted models, lower SPPB scores were significantly associated with more time/day spent sitting and watching television or resting (ɮ =-0.16 hours; 95% Confidence Interval (CI): -.024, -0.08 for TV watching and ɮ =-0.63 hours; 95% CI: -0.80, -0.46 for resting). Average time in computer use, eating, transportation, hobbies, or social activities did not differ by physical function level. Associations between physical function and sedentary time vary by the context. Social or engaging sedentary activities do not appear to be associated with physical function limitations in the same way as passive sedentary domains like television viewing and resting. Context should be considered in evaluating relationships of sedentary time with health outcomes.

A systematic review and meta-analysis of interventions to reduce sedentary behavior among older adults

2020 ◽  
Vol 10 (5) ◽  
pp. 1078-1085
Author(s):  
Jo-Ana D Chase ◽  
Jennifer Otmanowski ◽  
Sheri Rowland ◽  
Pamela S Cooper
Keyword(s):  
Public Health ◽  
Systematic Review ◽  
Older Adults ◽  
Health Outcomes ◽  
Sedentary Behavior ◽  
Sedentary Time ◽  
Meta Analysis ◽  
The United States ◽  
Future Research ◽  
Intervention Effects

Abstract Sedentary behavior (SB) is associated with numerous negative health outcomes, independent of physical activity behavior. Older adults are the most sedentary population in the United States. Understanding the effects and characteristics of existing interventions to reduce SB can inform practice, future research, and public health initiatives to improve older adults’ health. We conducted a systematic review and meta-analysis to examine existing SB intervention research among older adults and quantitatively synthesize intervention effects. Comprehensive searches were conducted to identify studies testing interventions to reduce SB time among adults at least 60 years old. Data on study design, intervention content and delivery, and participant characteristics were extracted from eligible studies. Standardized mean difference effect sizes (Cohen’s d) were synthesized using a random-effects model for two-group pretest–posttest design studies. Twenty-two reports describing 17 distinct studies were included in the narrative synthesis, with eight studies included in the meta-analysis (k = 8; n = 1,024). Most interventions were theory-driven and employed multiple strategies, including education, self-monitoring, and goal setting. Although SB interventions significantly reduced total sedentary time, the overall effect was small (d = −0.25, 95% confidence interval [−0.50, 0.00], p = .05). Studies were significantly heterogeneous (Q = 22.34, p < .01); however, the small number of comparisons prevented moderator analyses. Practitioners should employ diverse SB-specific strategies to encourage older adults to reduce time spent sedentary. To develop public health programs targeting SB in older adults, future research should include measures of time spent in specific SB and duration/number of breaks in sedentary time and investigate SB intervention effects on health outcomes.

scholarly journals Associations of breaks in sedentary time with abdominal obesity in Portuguese older adults

AGE ◽  
2015 ◽  
Vol 37 (2) ◽  
Author(s):  
Pedro B. Júdice ◽  
Analiza M. Silva ◽  
Diana A. Santos ◽  
Fátima Baptista ◽  
Luís B. Sardinha
Keyword(s):  
Older Adults ◽  
Abdominal Obesity ◽  
Sedentary Time ◽  
Breaks In Sedentary Time

Understanding Variations in the Health Consequences of Sedentary Behavior: A Taxonomy of Social Interaction, Novelty, Choice, and Cognition

2021 ◽  
pp. 1-9
Author(s):  
Wendell C. Taylor
Keyword(s):  
Older Adults ◽  
Social Interaction ◽  
Health Outcomes ◽  
Sedentary Behavior ◽  
Age Groups ◽  
Sedentary Behaviors ◽  
Positive Health ◽  
Adverse Health Outcomes ◽  
Important Challenge ◽  
Positive Health Outcomes

The study of sedentary behaviors requires taxonomies (classification schemes) to standardize data collection, measurements, and outcomes. Three taxonomies of sedentary behaviors have been identified, but none address an important challenge in sedentary behavior research, which is to distinguish between beneficial and detrimental health effects of various sedentary behaviors. Some sedentary behaviors (e.g., reading) are associated with positive health outcomes, whereas other sedentary behaviors (e.g., television viewing) are associated with adverse health outcomes. To address directly this complexity and present a different conception and understanding of discrepant findings related to health outcomes, a new taxonomy is needed. The development of the new taxonomy is guided by analysis of literature and selection of a relevant and informative behavioral sciences theoretical framework (i.e., self-determination theory). Because older adults are an increasing percentage of the population and report a high prevalence of sedentary behaviors, the new taxonomy was designed for older adults with potential application to all age groups. Taylor’s taxonomy of sedentary behaviors is parsimonious with four domains: social interaction (i.e., not solitary, companionship, interacting, and connecting with others); novelty (i.e., refreshingly new, unusual, or different); choice (i.e., volition, preferred option or alternative, the power, freedom, or decision to choose); and cognition (i.e., mentally stimulating and engaging).

Changes in Self-Reported Health and Psychosocial Outcomes in Older Adults Enrolled in Sedentary Behavior Intervention Study

2019 ◽  
Vol 33 (7) ◽  
pp. 1053-1057 ◽  
Author(s):  
Theresa E. Matson ◽  
Melissa L. Anderson ◽  
Anne D. Renz ◽  
Mikael Anne Greenwood-Hickman ◽  
Jennifer B. McClure ◽  
...  
Keyword(s):  
Older Adults ◽  
Health Outcomes ◽  
Sedentary Behavior ◽  
Psychosocial Factors ◽  
Self Efficacy ◽  
Behavior Intervention ◽  
Habit Strength ◽  
Sitting Time ◽  
Group I ◽  
Reported Health

Purpose: To estimate changes in self-reported health and psychosocial factors associated with a 12-week sedentary behavior intervention for older adults. Design: Exploratory secondary analysis of pilot randomized controlled trial. Setting: Kaiser Permanente Washington Subjects: Sixty adults aged 60 to 89 with body mass index ≥30 kg/m2. Intervention: Participants were randomized to the I-STAND intervention or control group. I-STAND involved 6 coaching sessions, a study workbook, Jawbone UP activity tracker to prompt breaks from sitting, and activPAL feedback on objective sitting time. Measures: At baseline and 12-week follow-up, participants completed a survey with validated measures of self-reported health outcomes (depression, stress, memory/concentration, sleep, pain, ability to do daily activities, energy, and quality of life) and modified scales measuring psychosocial factors (perceived benefits/barriers, social support, self-efficacy, and sedentary habit strength) regarding sedentary behavior. Analysis: Generalized linear models assessed associations between group assignment and change in each self-reported health and psychosocial score, adjusting for baseline scores. Results: I-STAND participants demonstrated improvements in self-efficacy (β = 0.35, 95% confidence interval [CI]: 0.10 to 0.60) and reduced habit strength (β= −0.23, 95% CI: −0.42 to −0.04) compared to control participants. There were no significant differences in self-reported health outcomes, although power was limited in this exploratory analysis. Conclusion: A sedentary behavior reduction intervention for older adults resulted in improvements for some psychosocial factors. Health outcomes may require longer than 12 weeks to observe improvements.

Acceptance and Feasibility of Seated Elliptical Pedaling to Replace Sedentary Behavior in Older Adults

2020 ◽  
Vol 28 (6) ◽  
pp. 844-853
Author(s):  
Nicholas L. Lerma ◽  
Chi C. Cho ◽  
Ann M. Swartz ◽  
Hotaka Maeda ◽  
Young Cho ◽  
...  
Keyword(s):  
Older Adults ◽  
Light Intensity ◽  
Health Outcomes ◽  
Sedentary Behavior ◽  
Activity Monitor ◽  
Group Differences ◽  
Significant Group ◽  
Significant Difference ◽  
The Impact

The purpose of this study was to explore the feasibility and acceptability of a seated pedaling device to reduce sedentary behavior (SB) in the homes of older adults. Methods: Each participant (N = 20) was outfitted with an activity monitor and seated pedaling device in the home for 7 days and randomly assigned to one of four light-intensity pedaling groups (15, 30, 45, and 60 min/day). Results: There was 100% adherence in all groups and significant group differences in the minutes pedaled per day (p < .001), with no significant difference in the total pedaling days completed (p = .241). The 15-, 30-, 45-, and 60-min groups experienced a 4.0%, 5.4%, 10.6%, and 11.3% reduction in SB on the days pedaled, respectively. Conclusion: Clinically relevant reductions in SB time were achievable in this 1-week trial. Long-term adherence and the impact of replacing SB with seated light activities on geriatric-relevant health outcomes should be investigated.

scholarly journals Walk Score® and Its Associations with Older Adults’ Health Behaviors and Outcomes

2019 ◽  
Vol 16 (4) ◽  
pp. 622 ◽  
Author(s):  
Yung Liao ◽  
Chien-Yu Lin ◽  
Ting-Fu Lai ◽  
Yen-Ju Chen ◽  
Bohyeon Kim ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Health Behaviors ◽  
Health Outcomes ◽  
Sedentary Time ◽  
Smoking Status ◽  
Lifestyle Behaviors ◽  
Tv Viewing ◽  
Health Lifestyle ◽  
Walk Score

This study aimed to investigate the associations between Walk Score® and lifestyle behaviors and health outcomes in older Taiwanese adults. A nationwide survey was conducted through telephone-based interviews with older adults (65 years and older) in Taiwan. Data on Walk Score®, lifestyle behaviors (physical activity, sedentary behavior, healthy eating behavior, alcohol use, and smoking status), health outcomes (overweight/obesity, hypertension, type 2 diabetes, and cardiovascular disease), and personal characteristics were obtained from 1052 respondents. A binary logistic regression adjusting for potential confounders was employed. None of the Walk Score® categories were related to the recommended levels of total physical activity. The categories “very walkable” and “walker’s paradise” were positively related to total sedentary time and TV viewing among older adults. No significant associations were found between Walk Score® and other lifestyle health behaviors or health outcomes. While Walk Score® was not associated with recommended levels of physical activity, it was positively related to prolonged sedentary time in the context of a non-Western country. The different associations between the walk score and health lifestyle behaviors and health outcomes in different contexts should be noted.

scholarly journals Are Area-Level Crimes Associated with Older Adults’ Physical Activity and Sedentary Behavior?

2019 ◽  
Vol 11 (9) ◽  
pp. 2454
Author(s):  
Chien-Yu Lin ◽  
Jong-Hwan Park ◽  
Ming-Chun Hsueh ◽  
Ting-Fu Lai ◽  
Yung Liao
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Sedentary Behavior ◽  
Sedentary Time ◽  
Binary Logistic Regression ◽  
Sociodemographic Factors ◽  
Behavior Interventions ◽  
Drug Crime ◽  
Residential Neighborhood ◽  
Crime Incidence

There is limited evidence for the associations of area-level crime with older adults’ physical activity and sedentary behavior, especially in Asia. This study explored the association of area-level crime with older adults’ active and sedentary behavior. A telephone-based survey of Taiwanese seniors was conducted in September–November of 2017. Data related to sociodemographic factors, residential neighborhood (objectively recorded area-level crime incidence), and time spent in physical activity and sedentary behavior, were obtained from 1068 older adults. Adjusted binary logistic regression was analyzed. Fully adjusted analyses showed older adults living in neighborhoods with a higher incidence of drug crime (odds ratio, OR = 0.71, 95% confidence interval, CI = 0.52–0.96), car theft (OR = 0.70, 95% CI 0.51–0.95), and locomotive theft (OR = 0.69, 95% CI 0.51–0.94) were found to be less likely to achieve the recommendation on physical activity. In addition, those living in neighborhoods with a higher incidence of theft (OR = 1.93, 95% CI 1.05–3.55), drug crime (OR = 1.93, 95% CI 1.05–3.55), breaking and entering (OR = 2.04, 95% CI 1.11–3.76), and rape (OR = 2.20, 95% CI 1.20–4.06) were more likely to have more sedentary time. There were sex differences in the association of area-level crime incidence with physical activity and sedentary behavior. These findings suggest that crime prevention should be considered when designing physical activity and sedentary behavior interventions for older adults.

Clinical and Ambulatory Gait Speed in Older Adults: Associations With Several Physical, Mental, and Cognitive Health Outcomes

2020 ◽  
Vol 100 (4) ◽  
pp. 718-727
Author(s):  
Miguel Á De la Cámara ◽  
Sara Higueras-Fresnillo ◽  
Kabir P Sadarangani ◽  
Irene Esteban-Cornejo ◽  
David Martinez-Gomez ◽  
...  
Keyword(s):  
Older Adults ◽  
Health Outcomes ◽  
Predictive Validity ◽  
Gait Speed ◽  
Well Being ◽  
Cognitive Status ◽  
Community Dwelling ◽  
Walk Test ◽  
Physical And Mental Health ◽  
Cognitive Health

Abstract Background Although clinical gait speed may indicate health and well-being in older adults, there is a lack of studies comparing clinical tests with ambulatory gait speed with regard to several health outcomes. Objective The objective of this study was to examine the associations of clinical gait speed, measured by the 2.44-m walk test and the ambulatory gait speed with several physical, mental, and cognitive health outcomes in older adults. Design A cross-sectional design was used. Methods The study population comprised 432 high-functioning, community-dwelling older adults (287 women) aged between 65 and 92 years. Clinical and ambulatory gait speeds were measured using the 2.44-m walk test and a portable gait analysis device, respectively. Multiple linear regressions were used to examine the association of clinical and ambulatory gait speeds with several health outcomes (body mass index, waist circumference, systolic and diastolic blood pressure, chronic conditions, self-rated health, exhaustion, upper- and lower-body strength, physical and mental health status, cognitive status, and self-rated cognitive status). Results The results showed that the average gait speed for clinical and ambulatory measures cannot be directly compared. Clinical gait speed was associated with 7 health outcomes, and the ambulatory gait speed was associated with 6 health outcomes. The significant associations between measures of gait speed and the health outcomes converged in 5 of the 13 health outcomes studied; however, the strength of associations was singly different between measures. Limitations The short monitoring time, the inability to distinguish between the ambulatory gait speed inside the home and outdoor gait speed, and the under-representative sample are limitations of the study. Conclusion The results indicated differences in the number and strength of associations between clinical and ambulatory gait speed. Both measures have construct validity because they have been associated with physical and health outcomes; however, they may have different predictive validity. Further research should be conducted to compare their predictive validity in longitudinal designs.

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